Prof. Dr. Rudolf Marcel Füchslin

Projects

• Blockchain-Enabled Financing of Supply Chains / Team member / ongoing
• Data-based Optimization of Outcomes: Successful Technology-Supported Therapy / Co-project leader / ongoing
• Next Generation 3D Tissue Models: Bio-Hybrid Hierarchical Organoid-Synthetic Tissues (Bio-HhOST) – Comprised of Live and Artificial Cells / Project leader / ongoing
• Bio-hybrid materials for bioprinting and tumour-targeted therapies (Bio-HhOST in ELM) / Co-project leader / ongoing
• Stability of self-organizing net fragments as inductive bias for next-generation deep learning / Team member / completed
• Neurological ICU Data / Project leader / completed
• Workshop European Centre for Living Technology / Project leader / completed
• AI powered CBCT for improved Combination Cancer Therapy / Team member / completed
• Automated Release Testing System / Project leader / completed
• Ecological and economic process optimization in cement production through machine learning / Team member / completed
• Extension SARS-CoV-2 Intervention modelling / Project leader / completed
• Creation of advanced cancer treatment planning to boost the effect of Radiotherapy by combining with hyperthermia, heating the tumor / Deputy project leader / completed
• Decision support for pandemics / Project leader / completed
• European Conference Series on Artificial Intelligence in Industry and Finance / Team member / completed
• Machine learning for NMR spectroscopy / Team member / completed
• SARS-CoV2 Modeling of Interventions on the Dynamics of the Pandemics / Project leader / completed
• DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Team member / completed
• Computational Archaeology / Project leader / completed
• SCIS Simulation Based Calibration of Infusion Systems / Project leader / completed
• Artificial Cells with Distributed Cores to Decipher Protein Function / Project leader / completed
• Data Driven Medical muscle Training / Project leader / completed
• Feasibility Study Reinforcement Learning for Heating Systems / Team member / completed
• 3rd European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• PhD Network in Data Science / Deputy project leader / completed
• Strategy planning for pandemics in Switzerland / Project leader / completed
• 2nd European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• Libra: A One-Tool Solution for MLD4 Compliance / Team member / completed
• Complexity 4.0 / Team member / completed
• Thermal Dosimetric Concept for Evaluating Synergistic Effect of Combined Hyperthermia-Radiotherapy / Co-project leader / completed
• Adaptive energy management system for buildings / Team member / completed
• 1st European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• Model of a Sieving machine (continuation) / Project leader / completed
• Model-based optimisation of combined anti-cancer therapy with heat and radiation / Team member / completed
• Dynamic in vivo profiling of DNA damage and -repair after ionizing radiation / Team member / completed
• SoE Project MPIG / Project leader / completed
• Econimo / Project leader / completed

Publications

Articles in scientific journal, peer-reviewed

• Baulin, V. A., Füchslin, R. M., Giacometti, A., Hauser, H., & Werner, M. (2026). Material‐based intelligence : autonomous adaptation and embodied computation in physical substrates. Advanced Intelligent Systems, e202501450. https://doi.org/10.1002/aisy.202501450
• Baulin, V. A., Giacometti, A., Fedosov, D. A., Ebbens, S. J., Varela-Rosales, N. R., Feliu, N., Chowdhury, M., Hu, M., Füchslin, R. M., Dijkstra, M., Mussel, M., Roij, R. v., Xie, D., Tzanov, V., Zu, M., Hidalgo-Caballero, S., Yuan, Y., Cocconi, L., Ghim, C.-M., et al. (2025). Intelligent soft matter : towards embodied intelligence. Soft Matter, 21(21), 4129–4145. https://doi.org/10.1039/d5sm00174a
• Bischof, L., Teodoropol, S., Füchslin, R. M., & Stockinger, K. (2025). Hybrid quantum neural networks show strongly reduced need for free parameters in entity matching. Scientific Reports, 15(1), 4318. https://doi.org/10.1038/s41598-025-88177-z
• Mingo Barba, S., Lobo-Cerna, F., Krawczyk, P. M., Lattuada, M., Füchslin, R. M., Petri-Fink, A., & Scheidegger, S. (2024). The use of survival dose-rate dependencies as theoretical discrimination criteria for in-silico dynamic radiobiological models. Dose-Response, 22(3). https://doi.org/10.1177/15593258241279906
• Dieper, A., Scheidegger, S., Füchslin, R. M., Veltsista, P. D., Stein, U., Weyland, M., Gerster, D., Beck, M., Bengtsson, O., Zips, D., & Ghadjar, P. (2024). Literature review: potential non-thermal molecular effects of external radiofrequency electromagnetic fields on cancer. International Journal of Hyperthermia, 41(1), 2379992. https://doi.org/10.1080/02656736.2024.2379992
• Mingo Barba, S., Ademaj, A., Marder, D., Riesterer, O., Lattuada, M., Füchslin, R. M., Petri-Fink, A., & Scheidegger, S. (2024). Theoretical evaluation of the impact of diverse treatment conditions by calculation of the tumor control probability (TCP) of simulated cervical cancer Hyperthermia-Radiotherapy (HT-RT) treatments in-silico. International Journal of Hyperthermia, 41(1), 2320852. https://doi.org/10.1080/02656736.2024.2320852
• Fankhauser, T., Solèr, M. E., Füchslin, R. M., & Stockinger, K. (2023). Multiple query optimization using a gate-based quantum computer. IEEE Access, 11, 114031–114043. https://doi.org/10.1109/ACCESS.2023.3324253
• Hostettler, M., Grüter, R., Stingelin, S. I., De Lorenzi, F., Füchslin, R. M., Jacomet, C., Koll, S., Wilhelm, D., & Boiger, G. K. (2023). Modelling of peristaltic pumps with respect to viscoelastic tube material properties and fatigue effects. Fluids, 8(9), 254–269. https://doi.org/10.3390/fluids8090254
• Amirian, M., Montoya-Zegarra, J. A., Herzig, I., Eggenberger Hotz, P., Lichtensteiger, L., Morf, M., Züst, A., Paysan, P., Peterlik, I., Scheib, S., Füchslin, R. M., Stadelmann, T., & Schilling, F.-P. (2023). Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks. Medical Physics, 50(10), 6228–6242. https://doi.org/10.1002/mp.16405
• Monteiro Simoes, R. D., Huber, P., Meier, N., Smailov, N., Füchslin, R. M., & Stockinger, K. (2023). Experimental evaluation of quantum machine learning algorithms. IEEE Access, 11, 6197–6208. https://doi.org/10.1109/ACCESS.2023.3236409
• Schilling, F.-P., Flumini, D., Füchslin, R. M., Gavagnin, E., Geller, A., Quarteroni, S., & Stadelmann, T. (2022). Foundations of Data Science : a comprehensive overview formed at the 1st International Symposium on the Science of Data Science. Archives of Data Science, Series A, 8(2). https://doi.org/10.5445/IR/1000146422
• Füchslin, R. M., & Flumini, D. (2022). AI as Arational Intelligence? Archives of Data Science, Series A, 8(2). https://doi.org/10.5445/IR/1000150236
• Viecelli, C., Aguayo, D., Dällenbach, S., Graf, D., Achermann, B., Hafen, E., & Füchslin, R. M. (2021). Algorithmic extraction of smartphone accelerometer-derived mechano-biological descriptors of resistance exercise is robust to changes in intensity and velocity. Plos One , 16(7), e0254164. https://doi.org/10.1371/journal.pone.0254164
• Viecelli, C., Graf, D., Aguayo, D., Hafen, E., & Füchslin, R. M. (2020). Using smartphone accelerometer data to obtain scientific mechanical-biological descriptors of resistance exercise training. Plos One, 15(7), e0235156. https://doi.org/10.1371/journal.pone.0235156
• Weyland, M. S., Thumser-Henner, P., Nytko, K. J., Rohrer Bley, C., Ulzega, S., Petri-Fink, A., Lattuada, M., Füchslin, R. M., & Scheidegger, S. (2020). Holistic view on cell survival and DNA damage : how model-based data analysis supports exploration of dynamics in biological systems. Computational and Mathematical Methods in Medicine, 2020. https://doi.org/10.1155/2020/5972594
• Bosch, J., Füchslin, R. M., & Zaugg, C. (2019). Multiple regimes in operation of the Swiss railway system and potential influences on power load. IEEE Transactions on Intelligent Transportation Systems, 20(5), 1697–1705. https://doi.org/10.1109/TITS.2018.2833961
• Schulz, N., Chaachouay, H., Nytko, K. J., Weyland, M. S., Roos, M., Füchslin, R. M., Guscetti, F., Scheidegger, S., & Rohrer Bley, C. (2017). Dynamic in vivo profiling of DNA damage and repair after radiotherapy using canine patients as a model. International Journal of Molecular Sciences, 18(6/1176). https://doi.org/10.3390/ijms18061176
• Baltensperger, T., Füchslin, R. M., Krütli, P., & Lygeros, J. (2017). European Union gas market development. Energy Economics, 66, 466–479. https://doi.org/10.1016/j.eneco.2017.07.002
• Miyashita, S., Audretsch, C., Nagy, Z., Füchslin, R. M., & Pfeifer, R. (2015). Mechanical catalysis on the centimetre scale. Journal of the Royal Society Interface, 12(104). https://doi.org/10.1098/rsif.2014.1271
• Baltensperger, T., Füchslin, R. M., Krütli, P., & Lygeros, J. (2015). Multiplicity of equilibria in conjectural variations models of natural gas markets. European Journal of Operational Research, 252(2). https://doi.org/10.1016/j.ejor.2016.01.032
• Füchslin, R. M., Dumont, E., Flumini, D., Fuchs, H. U., Hauser, H., Jaeger, C., Scheidegger, S., Schönenberger-Deuel, J., Lichtensteiger, L., Luchsinger, R. H., & Weyland, M. (2014). Morphological control : a design principle for applications in space science. Journal of the British Interplanetary Society, 67, 305–313. http://adsabs.harvard.edu/abs/2014JBIS...67..305F
• Fellermann, H., Krasnogor, N., Hadorn, M., & Füchslin, R. M. (2014). Formalizing modularization and data hiding in synthetic biology. ACM Journal on Emerging Technologies in Computing Systems, 11(3/24). https://doi.org/10.1145/2667231
• Füchslin, R. M., Dzyakanchuk, A., Flumini, D., Hauser, H., Hunt, K. J., Luchsinger, R. H., Reller, B., Scheidegger, S., & Walker, R. (2013). Morphological computation and morphological control : steps toward a formal theory and applications. Artificial Life, 19(1), 9–34. https://doi.org/10.1162/ARTL_a_00079
• Hauser, H., Sumioka, H., Füchslin, R. M., & Pfeifer, R. (2013). Introduction to the special issue on morphological computation. Artificial Life, 19(1), 1–8. https://doi.org/10.1162/ARTL_e_00083
• Weyland, M. S., Fellermann, H., Hadorn, M., Sorek, D., Lancet, D., Rasmussen, S., & Füchslin, R. M. (2013). The MATCHIT automaton : exploiting compartmentalization for the synthesis of branched polymers. Computational and Mathematical Methods in Medicine, 2013(467428). https://doi.org/10.1155/2013/467428
• Scheidegger, S., Fuchs, H. U., Zaugg, K., Bodis, S., & Füchslin, R. M. (2013). Using state variables to model the response of tumour cells to radiation and heat : a novel multi-hit-repair approach. Computational and Mathematical Methods in Medicine, 2013(587543). https://doi.org/10.1155/2013/587543
• Hauser, H., Ijspeert, A. J., Füchslin, R. M., Pfeifer, R., & Maass, W. (2012). The role of feedback in morphological computation with compliant bodies. Biological Cybernetics, 106(10), 595–613. https://doi.org/10.1007/s00422-012-0516-4
• Filisetti, A., Graudenzi, A., Serra, R., Villani, M., Füchslin, R. M., Packard, N., Kauffman, S. A., & Poli, I. (2012). A stochastic model of autocatalytic reaction networks. Theory in Biosciences, 131(2), 85–93. https://doi.org/10.1007/s12064-011-0136-x
• Nakajima, K., Tientcheu Ngouabeu, A. M., Miyashita, S., Göldi, M., Füchslin, R. M., & Pfeifer, R. (2012). Morphology-induced collective behaviors : dynamic pattern formation in water-floating elements. Plos One, 7(6/e37805). https://doi.org/10.1371/journal.pone.0037805
• Filisetti, A., Graudenzi, A., Serra, R., Villani, M., DeLucrezia, D., Füchslin, R. M., Kauffman, S. A., Packard, N., & Poli, I. (2011). A stochastic model of the emergence of autocatalytic cycles. Journal of Systems Chemistry, 2(2). https://doi.org/10.1186/1759-2208-2-2
• Hauser, H., Ijspeert, A. J., Füchslin, R. M., Pfeifer, R., & Maass, W. (2011). Towards a theoretical foundation for morphological computation with compliant bodies. Biological Cybernetics, 105(5-6), 355–370. https://doi.org/10.1007/s00422-012-0471-0

Books, peer-reviewed

• Hauser, H., Füchslin, R. M., & Pfeifer, R. (2014). Opinions and outlooks on morphological computation. Universität Zürich. https://doi.org/10.21256/zhaw-3157
• Serra, R., Füchslin, R. M., Schultes, E., & Villani, M. (2013). Complex systems models in biology and medicine : generic properties and applications. Hindawi. https://doi.org/10.1155/2014/580509

Book chapters, peer-reviewed

• Hollenstein, L., Lichtensteiger, L., Stadelmann, T., Amirian, M., Budde, L., Meierhofer, J., Füchslin, R. M., & Friedli, T. (2019). Unsupervised learning and simulation for complexity management in business operations. In M. Braschler, T. Stadelmann, & K. Stockinger (Eds.), Applied data science : lessons learned for the data-driven business (pp. 313–331). Springer. https://doi.org/10.1007/978-3-030-11821-1_17
• Miyashita, S., Tientcheu Ngouabeu, A. M., Füchslin, R. M., Nakajima, K., Audretsch, C., & Pfeifer, R. (2011). Basic problems in self-assembling robots and a case study of segregation on tribolon platform. In Y. Meng & J. Yaochu (Eds.), Bio-inspired self-organizing robotic systems (pp. 173–191). Springer. https://doi.org/10.1007/978-3-642-20760-0_8

Written conference contributions, peer-reviewed

• Peterko, Y., Spiess, M., Deblock-Bellamy, A., Füchslin, R., Aryananda Blatter, L., Quaaden, K., Berger, M., & Kaelin, V. (2025, October). “So, why did you do that?” : exploring therapists’ reasoning and decision-making in the use of technology for neurorehabilitation: a preliminary analysis. MiNT UK 2025 “Neurotechnology in Practice: Measuring Impact on Patient Outcomes”, London, United Kingdom, 16 October 2025. https://doi.org/10.21256/zhaw-34707
• Schmid, N., Wanner, M., Fischetti, G., Meshkian, M., Bruderer, S., Henrici, A., Füchslin, R. M., Wegner, J. D., Sigel, R. K. O., Heitmann, B., & Wilhelm, D. (2025, July 6). MolDETR : next-generation analysis of molecular spectra with deep learning. 21st European Magnetic Resonance Congress (EUROMAR), Oulu, Finnland, 6-10 July 2025. https://doi.org/10.21256/zhaw-33659
• Bolt, P., Ziebart, V., Jaeger, C., Schmid, N., Stadelmann, T., & Füchslin, R. M. (2024). A simulation study on energy optimization in building control with reinforcement learning [Conference paper]. In C. Y. Suen, A. Krzyzak, M. Ravanelli, E. Trentin, C. Subakan, & N. Nobile (Eds.), Artificial Neural Networks in Pattern Recognition. Springer. https://doi.org/10.1007/978-3-031-71602-7_27
• Mingo Barba, S., Ademaj, A., Marder, D., Riesterer, O., Lattuada, M., Füchslin, R. M., Fink, A., & Scheidegger, S. (2023). Tumor Control Probability (TCP) study to theoretically assess the impact of different clinical conditions in Hyperthermia plus Radiotherapy (HT+RT) treatments. 35th Annual Meeting European Society for Hyperthermic Oncology, Cologne, Germany, 26-29 September 2023.
• Weyland, M. S., Flumini, D., Schneider, J. J., Faggian, A., Patiño Diaz, A., & Füchslin, R. M. (2023). A chemical compiler for the synthesis of branched oligomers on standardized chemical reaction structures [Conference paper]. ALIFE 2023: Ghost in the Machine : Proceedings of the 2023 Artificial Life Conference, 105. https://doi.org/10.1162/isal_a_00648
• Scheidegger, S., Füchslin, R. M., & Gaipl, U. S. (2023). Multi – vs. single – perceptron approach for modelling the pattern recognition and classification in a multi-compartment adaptive immune system model [Conference paper]. ALIFE 2023: Ghost in the Machine : Proceedings of the 2023 Artificial Life Conference, 7. https://doi.org/10.1162/isal_a_00574
• Schneider, J. J., Faggian, A., Jamieson, W. D., Weyland, M. S., Li, J., Castell, O., Matuttis, H.-G., Barrow, D. A., Patiño Diaz, A., Sanahuja, L. C., Holler, S., Casiraghi, F., Hanczyc, M. M., Flumini, D., Eggenberger Hotz, P., & Füchslin, R. M. (2023). Artificial chemistry performed in an agglomeration of droplets with restricted molecule transfer [Conference paper]. In C. De Stefano, F. Fontanella, & L. Vanneschi (Eds.), Artificial Life and Evolutionary Computation (pp. 107–118). Springer. https://doi.org/10.1007/978-3-031-31183-3_9
• Matuttis, H.-G., Schneider, J. J., Li, J., Barrow, D. A., Faggian, A., Patiño Diaz, A., Holler, S., Casiraghi, F., Sanahuja, L. C., Hanczyc, M. M., Weyland, M. S., Flumini, D., Eggenberger Hotz, P., Dimitriou, P., Jamieson, W. D., Castell, O., & Füchslin, R. M. (2023). Computational investigation of the clustering of droplets in widening pipe geometries [Conference paper]. In C. De Stefano, F. Fontanella, & L. Vanneschi (Eds.), Artificial Life and Evolutionary Computation (pp. 82–93). Springer. https://doi.org/10.1007/978-3-031-31183-3_7
• Schneider, J. J., Faggian, A., Patiño Diaz, A., Li, J., Holler, S., Casiraghi, F., Sanahuja, L. C., Matuttis, H.-G., Hanczyc, M. M., Barrow, D. A., Weyland, M. S., Flumini, D., Eggenberger Hotz, P., Dimitriou, P., Jamieson, W. D., Castell, O., Eschle, P., & Füchslin, R. M. (2023). Network creation during agglomeration processes of polydisperse and monodisperse systems of droplets [Conference paper]. In C. De Stefano, F. Fontanella, & L. Vanneschi (Eds.), Artificial Life and Evolutionary Computation (pp. 94–106). Springer. https://doi.org/10.1007/978-3-031-31183-3_8
• Matuttis, H.-G., Holler, S., Casiraghi, F., Schneider, J. J., Faggian, A., Füchslin, R. M., & Hanczyc, M. M. (2023). The good, the bad and the ugly : droplet recognition by a “shootout”-heuristics [Conference paper]. Artificial Life and Evolutionary Computation, 51–62. https://doi.org/10.1007/978-3-031-23929-8_5
• Schneider, J. J., Faggian, A., Matuttis, H.-G., Barrow, D. A., Li, J., Holler, S., Casiraghi, F., Cebolla Sanahuja, L., Hanczyc, M. M., Eschle, P., Weyland, M. S., Flumini, D., Eggenberger Hotz, P., & Füchslin, R. M. (2023, January 22). Obstacles on the pathway towards chemical programmability using agglomerations of droplets. Artificial Life and Evolutionary Computation. https://doi.org/10.1007/978-3-031-23929-8_4
• Füchslin, R. M., Ambühl, J., Faggian, A., Fellermann, H. M., Flumini, D., Geller, A., Hanczyc, M. M., Klinkert, A., Krütli, P., Matuttis, H.-G., Ott, T., Scheidegger, S., Schmid, G. B., Smieszek, T., Schneider, J. J., Steiner, A., & Weyland, M. S. (2023, January 22). Ethical aspects of computational modelling in science, decision support and communication. Artificial Life and Evolutionary Computation. https://doi.org/10.1007/978-3-031-23929-8_24
• Schneider, J. J., Barrow, D. A., Li, J., Weyland, M. S., Flumini, D., Eggenberger Hotz, P., & Füchslin, R. M. (2023, January 22). Geometric restrictions to the agglomeration of spherical particles. Artificial Life and Evolutionary Computation. https://doi.org/10.1007/978-3-031-23929-8_7
• Schneider, J. J., Weyland, M. S., Flumini, D., & Füchslin, R. M. (2023, January 22). Exploring the three-dimensional arrangement of droplets. Artificial Life and Evolutionary Computation. https://doi.org/10.1007/978-3-031-23929-8_6
• Schneider, J. J., Lang, A., Hirtreiter, C., Morgenstern, I., & Füchslin, R. M. (2023, January 22). Investigation of the Ramsey-Pierce-Bowman model. Artificial Life and Evolutionary Computation. https://doi.org/10.1007/978-3-031-23929-8_23
• Artificial Life and Evolutionary Computation : 15th Italian Workshop, WIVACE 2021, Winterthur, Switzerland, September 15–17, 2021. (2023). In J. J. Schneider, M. S. Weyland, D. Flumini, & R. M. Füchslin (Eds.), XV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021. Springer. https://doi.org/10.1007/978-3-031-23929-8
• Hotz, P. E., Schneider, J. J., Casiraghi, F., Holler, S., Hanczyc, M. M., & Füchslin, R. M. (2022). Simulations of vesicular disentanglement [Conference paper]. In S. Holler, R. Löffler, & S. Bartlett (Eds.), ALIFE 2022: The 2022 Conference on Artificial Life (p. 25). MIT Press. https://doi.org/10.1162/isal_a_00505
• Mingo Barba, S., Lattuada, M., Füchslin, R. M., Fink, A., & Scheidegger, S. (2022). Repair protein damage vs. cell repair saturation : a comparison of its use in radiobiological models. 26th Annual SASRO Meeting, Baden, Switzerland, 1-3 September 2022.
• Herzig, I., Paysan, P., Scheib, S., Züst, A., Schilling, F.-P., Montoya, J., Amirian, M., Stadelmann, T., Eggenberger Hotz, P., Füchslin, R. M., & Lichtensteiger, L. (2022). Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT [Conference poster]. Medical Physics, 49(6), e325–e326. https://doi.org/10.1002/mp.15769
• Schneider, J. J., Faggian, A., Holler, S., Casiraghi, F., Li, J., Cebolla Sanahuja, L., Matuttis, H.-G., Hanczyc, M. M., Barrow, D. A., Weyland, M. S., Flumini, D., Eggenberger Hotz, P., & Füchslin, R. M. (2021). Influence of the geometry on the agglomeration of a polydisperse binary system of spherical particles [Conference paper]. ALIFE 2021: The 2021 Conference on Artificial Life, 71. https://doi.org/10.1162/isal_a_00392
• Chehda Moreno, N., Weyland, M., Smieszek, T., Füchslin, R. M., Krütli, P., Schneider, J. J., & Scheidegger, S. (2021, November 30). Interpreting difference measures for social contact matrices : impact on the pandemic dynamics. 8th International Conference on Infectious Disease Dynamics (Epidemics8), Online, 30 November - 3 December 2021.
• Flumini, D., Weyland, M. S., Schneider, J. J., Fellermann, H., & Füchslin, R. M. (2020). Towards programmable chemistries [Conference paper]. In F. Cicirelli, A. Guerrieri, C. Pizzuti, A. Socievole, G. Spezzano, & A. Vinci (Eds.), Artificial Life and Evolutionary Computation. Springer. https://doi.org/10.1007/978-3-030-45016-8_15
• Schneider, J. J., Weyland, M. S., Flumini, D., Matuttis, H.-G., Morgenstern, I., & Füchslin, R. M. (2020). Studying and simulating the three-dimensional arrangement of droplets [Conference paper]. In F. Cicirelli, A. Guerrieri, C. Pizzuti, A. Socievole, G. Spezzano, & A. Vinci (Eds.), Artificial Life and Evolutionary Computation. Springer. https://doi.org/10.1007/978-3-030-45016-8_16
• Gygax, G., Füchslin, R. M., & Ott, T. (2020). Self-organized division of labor in networks of forecasting models for time series with regime switches [Conference paper]. Proceedings of the NOLTA 2020 Conference, 278–281.
• Schneider, J. J., Weyland, M. S., Flumini, D., & Füchslin, R. M. (2020). Investigating three-dimensional arrangements of droplets [Conference paper]. In F. Cicirelli, A. Guerrieri, C. Pizzuti, A. Socievole, G. Spezzano, & A. Vinci (Eds.), Artificial Life and Evolutionary Computation (pp. 171–184). Springer. https://doi.org/10.1007/978-3-030-45016-8_17
• Weyland, M., Thumser-Henner, P., Rohrer Bley, C., Ulzega, S., Petri-Fink, A., Lattuada, M., Scheidegger, S., & Füchslin, R. M. (2019). Dynamic DNA damage and repair modelling : bridging the gap between experimental damage readout and model structure [Conference paper]. In S. Cagnoni, M. Mordonini, R. Pecori, A. Roli, & M. Villani (Eds.), Artificial Life and Evolutionary Computation (pp. 127–137). Springer. https://doi.org/10.1007/978-3-030-21733-4_10
• Schneider, J. J., Weyland, M., Flumini, D., & Füchslin, R. M. (2019, August). Simulation of a microfluidic system of droplets. Joint Annual Meeting of the Swiss Physical Society and the Austrian Physical Society, Zurich, 26-30 August 2019.
• Alife 2019 : proceedings of the Artificial Life Conference 2019. (2019). In H. Fellermann, J. Bacardit, Á. Goñi-Moreno, & R. M. Füchslin (Eds.), The 2019 Conference on Artificial Life, Newcastle, United Kingdom, 29 July - 2 August 2019. Massachusetts Institute of Technology. https://doi.org/10.1162/isal_a_00240
• Fellermann, H., Bacardit, J., Goñi-Moreno, A., & Füchslin, R. M. (2019, July). Artificial life in a challenged world. Proceedings of the Artificial Life Conference 2019. https://doi.org/10.1162/isal_a_00123
• Fellermann, H., Penn, A. S., Füchslin, R. M., Bacardit, J., & Goñi-Moreno, A. (2019). Towards low-carbon conferencing : acceptance of virtual conferencing solutions and other sustainability measures in the ALIFE community [Conference paper]. In H. Fellermann, J. Bacardit, A. Goñi-Moreno, & R. M. Füchslin (Eds.), Proceedings of the Artificial Life Conference 2019 (pp. 21–27). Massachusetts Institute of Technology. https://doi.org/10.1162/isal_a_00133
• Füchslin, R. M., Schneider, J. J., Ott, T., & Walker, R. (2019). Simplified modeling of the evolution of skills in a spatially resolved environment [Conference paper]. In H. Fellermann, J. Bacardit, A. Goñi-Moreno, & R. M. Füchslin (Eds.), Proceedings of the Artificial Life Conference 2019 (pp. 324–330). Massachusetts Institute of Technology. https://doi.org/10.1162/isal_a_00182
• Bolt, P., Ziebart, V., Jaeger, C., Ritzmann, R., Meier, O., & Füchslin, R. M. (2018). Model predictive control for building automation [Conference paper]. EuroSun 2018 : Conference Proceedings, 1330–1341. https://doi.org/10.18086/eurosun2018.11.05
• Scheidegger, S., Füchslin, R. M., Timm, O., Eberle, B., & Bodis, S. (2015). A novel approach for thermal dosimetry [Conference paper]. Proceedings of the ESHO Annual Meeting 2015, 26.
• Chaachouay, H., Scheidegger, S., Schulz, N., Grosse, N., Füchslin, R. M., van Loon, B., & Rohrer Bley, C. (2015). Monitoring of DNA damage and repair kinetics during radiotherapy in vivo : a minimally invasive approach using the dog as a model [Conference poster]. Molecular Radiation Biology/Oncology : Proceedings of 14th International Wolfsbergmeeting, 22.
• Jaeger, C., Housseini, R., Hertwig, M., Hofer, T., & Füchslin, R. M. (2014). Performance prediction and optimization for industrial sieves by simulation : a two-tier approach [Conference paper]. In C. Deatcu & J. Wittman (Eds.), ASIM 2014: 22. Symposium Simulationstechnik: 3. bis 5. September 2014: HTW Berlin: 2, Tagungsband: Teil II (pp. 299–306). Argesim. https://doi.org/10.21256/zhaw-1653
• Scheidegger, S., Fuchs, H. U., & Füchslin, R. M. (2014). Computational methods for exploring the dynamics of cancer : the potential of state variables for description of complex biological systems [Conference paper]. Proceedings of the International Symposium on Nonlinear Theory and Its Applications : NOLTA2014, Luzern, Switzerland, September 14-18, 2014, 168–171. https://doi.org/10.21256/zhaw-1764
• Scheidegger, S., Grosse, N., & Füchslin, R. M. (2014). Homologous recombination in the view of the MHR-model [Conference paper]. In S. Klöck (Ed.), Joint conference of the SSRMP, DGMP, ÖGMP : Dreiländertagung der Medizinischen Physik - Abstractbook (pp. 194–195). SGSMP/DGMP/ÖGMP.
• Bernhardsgrütter, R., Senn, C. W., Füchslin, R. M., Jaeger, C., Nakajima, K., & Hauser, H. (2014). Employing L-systems to generate mass-spring networks for morphological computing [Conference paper]. Proceedings of the 2014 International Symposium on Nonlinear Theory and Its Applications (NOLTA2014), 168–171. https://doi.org/10.21256/zhaw-1660
• Scheidegger, S., Lomax, N., Timm, O., Datta, N., Füchslin, R. M., & Bodis, S. (2013). Characterization of hyperthermia with radiotherapy : temporal homogeneity and limitations of the CEM concept [Conference paper]. Proceedings of the 28th Annual Meeting of the European Society for Hyperthermic Oncology 2013, 131.
• Scheidegger, S., Füchslin, R. M., Lutters, G., & Bodis, S. (2012). Dynamic modelling of the synergistic effect of hyperthermia and radiotherapy [Conference poster]. Radiotherapy & Oncology, 103(Supplement 1), s356. https://doi.org/10.1016/S0167-8140(12)71237-9
• Buecheler, T., Lonigro, R., Füchslin, R. M., & Pfeifer, R. (2011). Modeling and simulating crowdsourcing as a complex biological system : human crowds manifesting collective intelligence on the internet [Conference paper]. In T. Lenaerts, M. Giacobini, H. Bersini, P. Bourgine, M. Dorigo, & R. Doursat (Eds.), Advances in artificial life, ECAL 2011 : proceedings of the eleventh European conference on the synthesis and simulation of living systems (pp. 109–116). MIT Press. https://doi.org/10.21256/zhaw-1672
• Füchslin, R. M., Luchsinger, R. H., Reller, B., Hauser, H., & Scheidegger, S. (2011). Morphological computation : applications on different scales exploiting classical and statistical mechanics [Conference paper]. Proceedings of the 2nd International Conference on Morphological Computation, 41–44.
• Scheidegger, S., & Füchslin, R. M. (2011). Kinetic model for dose equivalent : an efficient way to predict systems response of irradiated cells [Conference paper]. In R. Bödi & W. Maurer (Eds.), Proceedings of ASIM 2011 : Grundlagen, Methoden und Anwendungen in Modellbildung und Simulation. Arbeitsgemeinschaft Simulation. https://doi.org/10.21256/zhaw-3558
• Tientcheu Ngouabeu, A. M., Miyashita, S., Füchslin, R. M., Nakajima, K., Göldi, M., & Pfeifer, R. (2010). Self-organized segregation effect on self-assembling robots [Conference paper]. In H. Fellermann, M. Dörr, M. M. Hanczyc, L. Ladegaard Laursen, S. Maurer, D. Merkle, P. A. Monnard, K. Støy, & S. Rasmussen (Eds.), Artificial live XII : proceedings of the twelfth international conference on the synthesis and simulation of living systems (pp. 232–238). MIT Press. https://doi.org/10.21256/zhaw-4112
• Bücheler, T., Sieg, J. H., Füchslin, R. M., & Pfeifer, R. (2010). Crowdsourcing, open innovation and collective intelligence in the scientific method : a research agenda and operational framework [Conference paper]. In H. Fellermann, M. Dörr, M. M. Hanczyc, L. Ladegaard Laursen, S. Maurer, D. Merkle, P. A. Monnard, K. Stoy, & S. Rasmussen (Eds.), Artificial live XII : proceedings of the twelfth international conference on the synthesis and simulation of living systels (pp. 679–686). MIT Press. https://doi.org/10.21256/zhaw-4094
• Füchslin, R. M., Filisetti, A., Serra, R., Villani, M., DeLucrezia, D., & Poli, I. (2010). Dynamical stability of autocatalytic sets [Conference paper]. In H. Fellermann, M. Dörr, M. M. Hanczyc, L. Ladegaard Laursen, S. Maurer, D. Merkle, P. A. Monnard, K. Støy, & S. Rasmussen (Eds.), Artificial live XII : proceedings of the twelfth international conference on the synthesis and simulation of living systems (pp. 65–72). MIT Press. https://doi.org/10.21256/zhaw-4097

Other publications

• Peterko, Y., Spiess, M., Deblock-Bellamy, A., Füchslin, R., Aryananda Blatter, L., Berger, M., & Kaelin, V. (2025, June). User-centered design (UCD) of a clinical decision support system (CDSS) in neurorehabilitation : a study protocol. Summer School “Towards a Continuum of Technology-Assisted Therapy (TCTT)”, Brissago, Switzerland, 23-27 June 2025. https://doi.org/10.21256/zhaw-34708
• Artificial Intelligence in Finance and Industry : Volume II - Highlights from the 7th European Conference. (2023). In A. Henrici, P. Schwendner, P. Deflorin, D. Wilhelm, & R. M. Füchslin (Eds.), 7th European COST Conference on Artificial Intelligence in Industry and Finance, Winterthur, Switzerland, 28 September 2022. Frontiers Research Foundation. https://www.frontiersin.org/research-topics/38909/
• Henrici, A., Füchslin, R. M., & Schwendner, P. (2023). Editorial: Artificial Intelligence in Finance and Industry: volume II—highlights from the 7th European conference. Frontiers in Artificial Intelligence, 6(1267377). https://doi.org/10.3389/frai.2023.1267377
• Bolt, P., Künzi, R., Ziebart, V., Füchslin, R. M., Motich, M., Antoni, M., Finger, M.-A., & Bürki, M. (2023, January 11). Optimizing cement production by employing physics informed machine learning. Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. https://doi.org/10.21256/zhaw-26666
• Artificial Intelligence in Finance and Industry : highlights from 6 European COST conferences. (2022). In P. Deflorin, R. M. Füchslin, A. Henrici, J. Osterrieder, P. Schwendner, & D. Wilhelm (Eds.), 5th European COST Conference on Artificial Intelligence in Industry and Finance, Winterthur, Switzerland (online), 3 September 2020. Frontiers Research Foundation. https://www.frontiersin.org/research-topics/18514/
• Schneider, J. J., Faggian, A., Holler, S., Casiraghi, F., Li, J., Sanahuja, L. C., Matuttis, H.-G., Hanczyc, M. M., Barrow, D. A., Weyland, M. S., Flumini, D., Eggenberger Hotz, P., Eschle, P., Patiño Diaz, A., & Füchslin, R. M. (2022). Paths in a network of polydisperse spherical droplets [Conference paper]. ALIFE 2022: The 2022 Conference on Artificial Life, 23. https://doi.org/10.1162/isal_a_00502
• Füchslin, R. M., Krütli, P., Ott, T., Scheidegger, S., Schneider, J. J., Seric, M., Smieszek, T., & Weyland, M. S. (2022). Minimal models for spatially resolved population dynamics : applications to coexistence in multi – trait models [Conference paper]. ALIFE 2022: The 2022 Conference on Artificial Life, 75. https://doi.org/10.1162/isal_a_00504
• Füchslin, R. M. (2021). Cross Roads #21: Morphological Computation and Control. Cross Labs / Cross Compass. https://www.youtube.com/watch?v=BTgCp5iIllc&t=364s
• Weyland, M. S., Flumini, D., Schneider, J. J., & Füchslin, R. M. (2020). A compiler framework to derive microfluidic platforms for manufacturing hierarchical, compartmentalized structures that maximize yield of chemical reactions [Conference paper]. ALIFE 2020: The 2020 Conference on Artificial Life, 602–604. https://doi.org/10.1162/isal_a_00303
• Füchslin, R. M. (2020). AI = Arational Intelligence? ANG-Fokus, 2020(1), 26–29.
• Krütli, P., Smieszek, T., Füchslin, R. M., & Eschle, P. (2018). Prioritätenliste und Kontingentberechnung : Pandemievorbereitung in der Schweiz (2. Auflage). ETH Zürich. https://doi.org/10.21256/zhaw-5543
• Krütli, P., Smieszek, T., Füchslin, R. M., & Eschle, P. (2017). Liste des priorités et calcul des contingents : préparation aux pandémies en Suisse (2. Auflage). ETH Zürich. https://doi.org/10.21256/zhaw-5544
• Füchslin, R. M. (2016). Theory in the applied sciences, Invited talk Norbert Straumann to his 80th birthday, Seminar in Lavin, organized by Prof. Ruedi Stoop.
• Scheidegger, S., & Füchslin, R. M. (2014). In vitro, in vivo, in silico : Modellbildung und Computersimulation als komplementäre Labormethode. ANG Fokus, 1, 82–97.
• Füchslin, R. M. (2014). Morphological control as guiding principle in physiology and medical applications, Invited talk ShanghAI Lectures of Prof. Rolf Pfeifer.
• Füchslin, R. M. (2013). Morphological Control. Aktuelle Technik, 2013(8), 34–35. https://doi.org/10.21256/zhaw-1665
• Füchslin, R. M. (2012). Wozu brauchen wir Curiosity? Journal 21.

Oral conference contributions and abstracts

• Schneider, J. J., Barrow, D. A., Li, J., Weyland, M., Flumini, D., Eggenberger Hotz, P., & Füchslin, R. M. (2023, August 7). Bidisperse extension of the kissing number problem. 28th International Conference on Statistical Physics (Statphys28), Tokyo, Japan, 7-11 August 2023.
• Füchslin, R. M. (2022). Applied science : the curse and blessing of applying science. Talk at Newcastle University, Newcastle, United Kingdom, 15 March 2022.
• Mingo Barba, S., Lobo-Cerna, F., Lattuada, M., Füchslin, R. M., Fink, A., Krawcyk, P. M., & Scheidegger, S. (2022). The use of qualitative and quantitative hyperthermic effects as discrimination criteria in radiobiological models. 34th Annual Meeting European Society for Hyperthermic Oncology, Gothenburg, Sweden, 14-17 September 2022.
• Hostettler, M., Stingelin, S., De Lorenzi, F., Füchslin, R. M., Jacomet, C., Koll, S., Wilhelm, D., & Boiger, G. (2022). Modelling of peristaltic pumps for viscoelastic tube material properties under consideration of fatigue effects [Conference presentation]. Multiphysics 2022, 33. https://static1.squarespace.com/static/5c9f89c101232c1d41297d67/t/639912525a90a93394aa8b71/1670976084271/MULTIPHYSICS+2022-Abstract+Booklet.pdf
• Mingo Barba, S., Lattuada, M., Füchslin, R. M., Fink, A., & Scheidegger, S. (2022). The use of dose rate dependencies as a theoretical discrimination criteria in radiobiological models. 4th European Congress of Medical Physics, Dublin, Ireland, 17-20 August 2022.
• Fankhauser, T., Soler, M., Füchslin, R. M., & Stockinger, K. (2021). Implementing database and machine learning algorithms on publicly available quantum computers. Talk at Zurich University, Zurich, Switzerland, 4 May 2021.
• Schneider, J. J., Faggian, A., Holler, S., Casiraghi, F., Li, J., Cebolla Sanahuja, L., Matuttis, H.-G., Hanczyc, M. M., Barrow, D. A., Weyland, M. S., Flumini, D., Eggenberger Hotz, P., & Füchslin, R. M. (2021). Influence of the geometry on the agglomeration of a polydisperse binary system of spherical particles. International Conference on Artificial Life (ALIFE), Online, 19-23 July 2021. https://www.youtube.com/watch?v=2uSgimAHU4I
• Füchslin, R. M. (2021, September 16). Modeling social systems at ZHAW. XV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021.
• Füchslin, R. M. (2021, August 26). Computational approaches in biology. ACDC Summer School, Online, 26-27 August 2021.
• Weber, R., Mehmet, Y., Füchslin, R. M., & Stockinger, K. (2020, September 9). Quantum databases and quantum machine learning : how far can we go on a publicly available quantum computer? Datalab Seminar ZHAW, Winterthur, 9. September 2020. https://www.zhaw.ch/de/forschung/departementsuebergreifende-kooperationen/datalab/datalab-seminar/
• Füchslin, R. M., Scheidegger, S., Flumini, D., Schneider, J. J., & Weyland, M. (2019, December). Morphological computation and control in medicine and related sciences. BioDynaMo, Zurich, 2-3 December 2019.
• Schneider, J. J., Weyland, M., Flumini, D., & Füchslin, R. M. (2019, September 19). Exploring the three-dimensional arrangement of droplets. XIV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Rende, Italy, 18-20 September 2019.
• Schneider, J. J., & Füchslin, R. M. (2019, August 30). Simulations of artificial populations with competing skills. Joint Annual Meeting of the Swiss Physical Society and of the Austrian Physical Society, Zurich, 26-30 August 2019.
• Füchslin, R. M., Schneider, J. J., & Walker, R. (2019, July 29). Simplified modeling of the evolution of skills in a spatially resolved environment. The 2019 Conference on Artificial Life, Newcastle, United Kingdom, 29 July - 2 August 2019.
• Fellermann, H., Bacardit, J., Goñi-Moreno, Á., & Füchslin, R. M. (2019, July). 2019 Preface. Proceedings of the Artificial Life Conference 2019. https://doi.org/10.1162/isal_e_00239
• Weyland, M., Thumser-Henner, P., Rohrer Bley, C., Ulzega, S., Petri-Fink, A., Lattuada, M., Scheidegger, S., & Füchslin, R. M. (2018). Dynamic DNA damage and repair modeling : bridging the gap between experimental damage readout and model structure. XIII International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Parma, Italy, 10-12 September 2018.
• Füchslin, R. M. (2018, December 12). The role of models in applied sciences. Talk at SWISSNEX Meeting, Winterthur, 12. Dezember 2018.
• Füchslin, R. M. (2017, November 9). BionTec 2.0. Vortrag am TecDay an der Alten Kantonsschule Aarau, Aarau, 9. November 2017.
• Füchslin, R. M. (2017, September 29). Applied complex systems sciences : the role of models. Invited Talk at Swiss Banking Advisory Event, 29. September 2017.
• Füchslin, R. M. (2017, September 20). Applied complex systems sciences. WIVACE 2017 Book of Abstracts. https://wivace.org/2017/files/bookOfAbstracts.pdf
• Ott, T., & Füchslin, R. M. (2017, June 5). The future’s back : first generic models of self-defeating road traffic forecasting. NDES 2017, 25th Nonlinear Dynamics of Electronic Systems Conference, Zernez, 5-7 June 2017.
• Füchslin, R. M. (2017, March 13). Evolution als Werkzeug. Rotary Club Lenzburg, Lenzburg, 13. März 2017.
• Füchslin, R. M. (2015, November 13). Morphological control applied embodied intelligence in mechanical and biological systems offering new perspectives to creativity support systems. Proceedings the Tenth International Conference on Knowledge Information and Creativity Support Systems (KICSS 2015).
• Füchslin, R. M. (2015, August 4). Morphological control : applied embodied intelligence in medicine, robotics and IT. Vortrag ML - Meetup ETH, Zürich, 4. August 2015.
• Füchslin, R. M. (2014, December 10). Morphological computation and control : von der Robotik zur Funktion der Zelle. Vortrag Aargauische Naturforschende Gesellschaft, Aarau, 10. Dezember 2014.
• Füchslin, R. M. (2014, February 21). Morphological computation and control : von der Robotik zur Funktion der Zelle. Vortrag: Naturwissenschaftliche Gesellschaft Winterthur, Winterthur, 21. Februar 2014.
• Füchslin, R. M., Flumini, D., Hauser, H., Hunt, K. J., Luchsinger, R. H., & Scheidegger, S. (2013, July 19). Morphological control as guiding principle in physiology and medical applications. Int. Workshop on Soft Robotics and Morphological Computation, Ascona, 19 July 2013.
• Hadorn, M., Gil, B., Svaneborg, C., Hanczyc, M. M., Fellermann, H., Füchslin, R. M., Eggenberger Hotz, P., Kunstmann-Olsen, C., Lancet, D., McCaskill, J., Monnard, P.-A., von Kiedrowski, G., & Rasmussen, S. (2012). A minimal artificial subcellular matrix. 13th International Conference on the Simulation & Synthesis of Living Systems (Artificial Life 13), Michigan, USA, 19-22 July 2012.
• Scheidegger, S., Füchslin, R. M., Bodis, S., & Lutters, G. (2012). The dynamic view to hyperthermia : a comparison of the CEM43° concept [Conference presentation]. Strahlentherapie Und Onkologie, 188(8), 738. https://doi.org/10.1007/s00066-012-0181-5
• Füchslin, R. M. (2012, November 8). Morphological computation and control : from robotics to implications on anticancer treatment. Research Colloquium 2012, Aarau, 8. November 2012.
• Füchslin, R. M. (2011, September 12). Morphological control : applications on different scales exploiting classical and statistical mechanic. ICMC2011: 2nd International Conference on Morphological Computation, Venice, Italy, 12–14 September 2011.
• Füchslin, R. M. (2010, August 19). Controlling dynamical architecture contributions from morphological computation and control. Satellite Workshop of ALIFE XII, Odense, Denmark, 19 August 2010.

Research data

Enayati, Aref; Baird, Hannah; Weyland, Mathias; Fink, Alke; Lattuada, Marco, Alke; Jamieson, William; Füchslin, Rudolf M.; Castell, Oliver, . Enhanced quantitative accuracy in single molecule imaging : a fidelity-guided denoising approach. Zenodo. Available from: https://doi.org/10.5281/zenodo.19498257

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